MétaCan
Menu
Back to cohort
Record W2887080370

The Application of NURBS to Acoustical Science

2017· article· en· W2887080370 on OpenAlexaffvenueabout
John O’Keefe

Bibliographic record

VenueCanadian acoustics · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOpera houseCeiling (cloud)ArchitectureEngineeringOperaArchitectural engineeringArchitectural designConstruct (python library)Computer scienceEngineering drawingMechanical engineeringVisual artsStructural engineeringArt
DOInot available

Abstract

fetched live from OpenAlex

NURBS, or Non-Uniform Rational B-Splines, are essentially a 3-D expansion of a 2-D B-spline.  The mathematical construct was developed by the Italian automotive industry in the early 1960s.  Since then they have been used to design everything from children’s’ toys to opera houses.  The ceiling of Toronto’s opera house, the Four Seasons Centre for the Performing Arts, was designed with a software package called Rhino, which is based, mathematically, on NURBS.  This package allows architects and engineers to design not just within a rectilinear confinement but with the curved surfaces that have served us so well in the past.  An element that has sadly been missing in current architecture.  Partly because acousticians force architects into rectilinear expressions.   But it does not need to be that way.   NURBS now give a freedom of design in acoustics, architecture and so many other fields. A study of existing rooms with profoundly focusing elements will be presented, a geometrical explanation of basic focusing elements will be reviewed and, finally, the design thoughts on a recently opened Canadian hall will be discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.006
Scholarly communication0.0040.003
Open science0.0020.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0130.007

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.247
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes3
Has abstractyes

Explore more

Same venueCanadian acousticsSame topic3D Surveying and Cultural HeritageFrench-language works237,207